Dbt

As explained in Effective Data Analysis

dbt is an open-source tool that enables analytics engineers to transform data in a warehouse using SQL-based projects, testing, documentation, and software-development practices.

dbt is a SQL-centered tool for helping data teams collaboratively define and transform warehouse schemas and tables. It reduces the need to manage warehouse complexity directly. section 11.3.1

Teams use dbt models to:

• Create tables for a specific team, such as product metrics. section 11.3.1
• Expose data at source, analytics, and metrics layers with different levels of complexity. section 11.3.1
• Update and augment core warehouse sources with newly added information. section 11.3.1

A dbt model

A model’s .sql file combines table metadata, a SQL query, and Jinja templating syntax for referencing other dbt models or warehouse sources. section 11.3.1

Figure 11.12 dbt combines SQL, table metadata, and Jinja templating syntax to define tables.

The figure shows how SQL, table metadata, and Jinja templating syntax combine to define a table. section 11.3.1

How Effective Data Analysis covers it

How deep it goes

Explains models through metadata, SQL, and Jinja references, but stops short of detailed warehouse implementation or advanced dbt features.

Examples

Uses product-team metrics, source-to-metrics layers, and a model file combining SQL, metadata, and Jinja.

What it assumes

Assumes comfort writing SQL and introduces table metadata and Jinja references within model files.

What you can do after

Apply dbt to define warehouse tables for teams, organize data into layers, and reference related models or sources.

How it connects

Connects SQL with data warehouses, schemas, tables, data layers, and Jinja templating.

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Also explained in

• 

  liveBookmanning.com
  DuckDB in Actiondbt is an SQL-centric transformation tool for building, testing, documenting, and deploying modular data models and pipelines.
• 

  liveBookmanning.com
  Architecting an Apache Iceberg Lakehousedbt is an open-source tool for transforming data in analytical data warehouses and lakehouses using SQL-based models, testing, and documentation.

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Related concepts

• analytics engineeringused by · Analytics engineering is the function of developing and maintaining transformed data models and analytical data infrastructure.
• Jinjauses · Jinja is a Python templating engine that generates text by rendering templates containing static content, expressions, variables, and control structures with supplied data.
• SQLuses · SQL is a standardized declarative language for defining, querying, and manipulating data in relational database systems.

This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.